Ultrasound imaging with real-time visual feedback for cardiopulmonary resuscitation (cpr) compressions

ABSTRACT

Systems and methods are provided for ultrasound imaging with real-time feedback for cardiopulmonary resuscitation (CPR) compressions. Ultrasound images generated based on received echo ultrasound signals during cardiopulmonary resuscitation (CPR) of a patient may be processed, and based on the processing of the ultrasound images, real-time information relating to the cardiopulmonary resuscitation (CPR) may be determined. Feedback for assisting in conducting the cardiopulmonary resuscitation (CPR) may be generated based on the information. The feedback may include information and/or indications relating to compressions applied during the cardiopulmonary resuscitation (CPR). The feedback may be configured for outputting during displaying of the generated ultrasound images

FIELD

Aspects of the present disclosure relate to medical imaging. Morespecifically, certain embodiments relate to methods and systems forultrasound imaging with real-time feedback for cardiopulmonaryresuscitation (CPR) compressions.

BACKGROUND

Various medical imaging techniques may be used, such as in imagingorgans and soft tissues in a human body. Examples of medical imagingtechniques include ultrasound imaging, computed tomography (CT) scans,magnetic resonance imaging (MRI), etc. The manner by which images aregenerated during medical imaging depends on the particular technique.

For example, ultrasound imaging uses real time, non-invasive highfrequency sound waves to produce ultrasound images, typically of organs,tissues, objects (e.g., fetus) inside the human body. Images produced orgenerated during medical imaging may be two-dimensional (2D),three-dimensional (3D), and/or four-dimensional (4D) images (essentiallyreal-time/continuous 3D images). During medical imaging, imagingdatasets (including, e.g., volumetric imaging datasets during 3D/4Dimaging) are acquired and used in generating and rendering correspondingimages (e.g., via a display) in real-time.

Various issues may exist with conventional approaches for utilizingmedical imaging. In this regard, conventional systems and methods, ifany existed, for utilizing medical imaging during cardiopulmonaryresuscitation (CPR), can be inefficient and/or ineffective.

Further limitations and disadvantages of conventional and traditionalapproaches will become apparent to one of skill in the art, throughcomparison of such systems with some aspects of the present disclosure,as set forth in the remainder of the present application with referenceto the drawings.

BRIEF SUMMARY

System and methods are provided for a ultrasound imaging with real-timefeedback for cardiopulmonary resuscitation (CPR) compressions,substantially as shown in and/or described in connection with at leastone of the figures, as set forth more completely in the claims.

These and other advantages, aspects and novel features of the presentdisclosure, as well as details of one or more illustrated exampleembodiments thereof, will be more fully understood from the followingdescription and drawings.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a block diagram illustrating an example medical imagingarrangement that supports ultrasound imaging with real-time feedback forcardiopulmonary resuscitation (CPR) compressions, in accordance with thepresent disclosure.

FIG. 2 is a block diagram illustrating an example ultrasound system thatsupports ultrasound imaging with real-time feedback for cardiopulmonaryresuscitation (CPR) compressions, in accordance with the presentdisclosure.

FIG. 3 illustrates an example ultrasound image showing the heart andsurrounding area, which may be generated via an ultrasound systemconfigured for supporting cardiopulmonary resuscitation (CPR) operationsin accordance with the present disclosure.

FIG. 4 illustrates example ultrasound images that incorporate real-timevisual feedback relating to location of cardiopulmonary resuscitation(CPR) compressions, in accordance with the present disclosure.

FIG. 5 illustrates example ultrasound image that incorporates real-timevisual feedback relating to location of and additional data pertainingto cardiopulmonary resuscitation (CPR) compressions, in accordance withthe present disclosure.

FIG. 6 illustrates a flowchart of an example steps that may be performedfor ultrasound imaging with ultrasound imaging with real-time feedbackfor cardiopulmonary resuscitation (CPR) compressions.

DETAILED DESCRIPTION

Certain implementations in accordance with the present disclosure may bedirected to ultrasound imaging with real-time feedback forcardiopulmonary resuscitation (CPR) compressions. In particular, variousembodiments have the technical effect of enhancing cardiopulmonaryresuscitation (CPR), by allowing for providing real-time feedbackrelating to cardiopulmonary resuscitation (CPR), particularly CPRcompressions. This may be done, for example, by processing ultrasoundimages (or datasets corresponding thereto) to identify structurespertinent to CPR compressions, tracking locations of compression,determining when the compressions (or majority thereof) are applied atcorrect position, and providing real-time feedback to users based ontracking of CPR compressions, particularly visually within displayedultrasound images.

The foregoing summary, as well as the following detailed description ofcertain embodiments will be better understood when read in conjunctionwith the appended drawings. To the extent that the figures illustratediagrams of the functional blocks of various embodiments, the functionalblocks are not necessarily indicative of the division between hardwarecircuitry. Thus, for example, one or more of the functional blocks(e.g., processors or memories) may be implemented in a single piece ofhardware (e.g., a general purpose signal processor or a block of randomaccess memory, hard disk, or the like) or multiple pieces of hardware.Similarly, the programs may be stand-alone programs, may be incorporatedas subroutines in an operating system, may be functions in an installedsoftware package, and the like. It should be understood that the variousembodiments are not limited to the arrangements and instrumentalityshown in the drawings. It should also be understood that the embodimentsmay be combined, or that other embodiments may be utilized and thatstructural, logical and electrical changes may be made without departingfrom the scope of the various embodiments. The following detaileddescription is, therefore, not to be taken in a limiting sense, and thescope of the present disclosure is defined by the appended claims andtheir equivalents.

As used herein, an element or step recited in the singular and precededwith the word “a” or “an” should be understood as not excluding pluralof said elements or steps, unless such exclusion is explicitly stated.Furthermore, references to “an exemplary embodiment,” “variousembodiments,” “certain embodiments,” “a representative embodiment,” andthe like are not intended to be interpreted as excluding the existenceof additional embodiments that also incorporate the recited features.Moreover, unless explicitly stated to the contrary, embodiments“comprising,” “including,” or “having” an element or a plurality ofelements having a particular property may include additional elementsnot having that property.

Also as used herein, the term “image” broadly refers to both viewableimages and data representing a viewable image. However, many embodimentsgenerate (or are configured to generate) at least one viewable image. Inaddition, as used herein, the phrase “image” is used to refer to anultrasound mode such as B-mode (2D mode), M-mode, three-dimensional (3D)mode, CF-mode, PW Doppler, CW Doppler, MGD, and/or sub-modes of B-modeand/or CF such as Shear Wave Elasticity Imaging (SWEI), TVI, Angio,B-flow, BMI, BMI_Angio, and in some cases also MM, CM, TVD where the“image” and/or “plane” includes a single beam or multiple beams.

In addition, as used herein, the phrase “pixel” also includesembodiments where the data is represented by a “voxel.” Thus, both theterms “pixel” and “voxel” may be used interchangeably throughout thisdocument.

Furthermore, the term processor or processing unit, as used herein,refers to any type of processing unit that can carry out the requiredcalculations needed for the various embodiments, such as single ormulti-core: CPU, Accelerated Processing Unit (APU), Graphics Board, DSP,FPGA, ASIC or a combination thereof.

It should be noted that various embodiments described herein thatgenerate or form images may include processing for forming images thatin some embodiments includes beamforming and in other embodiments doesnot include beamforming. For example, an image can be formed withoutbeamforming, such as by multiplying the matrix of demodulated data by amatrix of coefficients so that the product is the image, and wherein theprocess does not form any “beams”. In addition, forming of images may beperformed using channel combinations that may originate from more thanone transmit event (e.g., synthetic aperture techniques).

In various embodiments, ultrasound processing to form images isperformed, for example, including ultrasound beamforming, such asreceive beamforming, in software, firmware, hardware, or a combinationthereof. One implementation of an ultrasound system having a softwarebeamformer architecture formed in accordance with various embodiments isillustrated in FIGS. 1 and 2.

FIG. 1 is a block diagram illustrating an example medical imagingarrangement that supports ultrasound imaging with real-time feedback forcardiopulmonary resuscitation (CPR) compressions, in accordance with thepresent disclosure. Shown in FIG. 1 is an example setup 100 thatcomprises one or more medical imaging systems 110 and one or morecomputing systems 120.

The medical imaging system 110 comprise suitable hardware, software, ora combination thereof, for supporting medical imaging—that is enablingobtaining data used in generating and/or rendering images during medicalimaging exams. This may entail capturing of particular type of data, inparticular manner, which may in turn be used in generating data for theimages. For example, the medical imaging system 110 may be an ultrasoundsystem, configured for generating and/or rendering ultrasound images. Anexample implementation of an ultrasound system, which may correspond tothe medical imaging system 110, is described in more detail with respectto FIG. 2.

As shown in FIG. 1, the medical imaging system 110 may comprise a probe112, which may be portable and movable, and a display/control unit 114.The probe 112 may be configured for generating and/or capturingparticular type of signals (or data corresponding thereto), such as bybeing moved over a patient's body (or part thereof). For example, wherethe medical imaging system 110 is an ultrasound system, the probe 112may emit ultrasound signals and capture echo ultrasound images.

The display/control unit 114 may be configured for displaying images(e.g., via a screen 116). In some instances, the display/control unit114 may further be configured for generating the displayed images, atleast partly. Further, the display/control unit 114 may also supportuser input/output. For example, the display/control unit 114 may provide(e.g., via the screen 116), in addition to the images, user feedback(e.g., information relating to the system, functions thereof, settingsthereof, etc.). The display/control unit 114 may also support user input(e.g., via user controls 118), such as to allow controlling of themedical imaging. The user input may be directed to controlling displayof images, selecting settings, specifying user preferences, requestingfeedback, etc.

In some implementation, the medical imaging system 110 may alsoincorporate additional and dedicated computing resources, such as theone or more computing systems 120. In this regard, each computing system120 may comprise suitable circuitry, interfaces, logic, and/or code forprocessing, storing, and/or communication data. The computing system 120may be dedicated equipment configured particularly for use inconjunction with medical imaging, or it may be a general purposecomputing system (e.g., personal computer, server, etc.) set up and/orconfigured to perform the operations described hereinafter with respectto the computing system 120. The computing system 120 may be configuredto support operations of the medical imaging systems 110, as describedbelow. In this regard, various functions and/or operations may beoffloaded from the imaging systems. This may be done to streamlineand/or centralize certain aspects of the processing, to reduce cost (byobviating the need to increase processing resources in the imagingsystems.

The computing systems 120 may be set up and/or arranged for use indifferent ways. For example, in some implementations a single computingsystem 120 may be used; in other implementations multiple computingsystems 120, either configured to work together (e.g., based ondistributed-processing configuration), or separately, with eachcomputing system 120 being configured to handle particular aspectsand/or functions, and/or to process data only for particular medicalimaging systems 110.

In some implementations, the computing systems 120 may be local (e.g.,co-located with one or more medical imaging systems 110, such within thesame facility and/or same local network); in other implementations, thecomputing systems 120 may be remote and thus can only be accessed viaremote connections (e.g., via the Internet or other available remoteaccess techniques). In a particular implementation, the computingsystems 120 may be configured in cloud-based manner, and may be accessedand/or used in substantially similar way that other Cloud-based systemsare accessed and used.

Once data is generated and/or configured in the computing system 120,the data may be copied and/or loaded into the medical imaging systems110. This may be done in different ways. For example, the data may beloaded via directed connections or links between the medical imagingsystems 110 and the computing system 120. In this regard, communicationsbetween the different elements in the setup 100 may be done usingavailable wired and/or wireless connections, and/or in accordance anysuitable communication (and/or networking) standards or protocols.Alternatively, or additionally, the data may be loaded into the medicalimaging systems 110 indirectly. For example, the data may be stored intosuitable machine readable media (e.g., flash card, etc.), which are thenused to load the data into the medical imaging systems 110 (on-site,such as by users of the systems or authorized personnel), or the datamay be downloaded into local communication-capable electronic devices(e.g., laptops, etc.), which are then used on-site (e.g., by users ofthe systems or authorized personnel) to upload the data into the medicalimaging systems 110, via direct connections (e.g., USB connector, etc.).

In operation, the medical imaging system 110 may be used in generatingand presenting (e.g., rendering or displaying) images during medicalexams, and/or in supporting user input/output in conjunction therewith.The images may be 2D, 3D, and/or 4D images. The particular operations orfunctions performed in the medical imaging system 110 to facilitate thegenerating and/or presenting of images depends on the type ofsystem—that is, the manner by which the data corresponding to the imagesis obtained and/or generated. For example, in ultrasound imaging, thedata is based on emitted and echo ultrasound signals, as described inmore detail with respect to FIG. 2.

In various implementations, the medical imaging system 110 may beconfigured to support real-time feedback for cardiopulmonaryresuscitation (CPR) compressions, as described below.

FIG. 2 is a block diagram illustrating an example ultrasound system thatsupports ultrasound imaging with real-time feedback for cardiopulmonaryresuscitation (CPR) compressions, in accordance with the presentdisclosure. Shown in FIG. 2 is an ultrasound system 200.

The ultrasound system 200 may be configured for providing ultrasoundimaging, and as such may comprise suitable circuitry, interfaces, logic,and/or code for performing and/or supporting ultrasound imaging relatedfunctions. The ultrasound system 200 may correspond to the medicalimaging system 110 of FIG. 1 in ultrasound imaging use scenarios.

The ultrasound system 200 comprises, for example, a transmitter 202, anultrasound probe 204, a transmit beamformer 210, a receiver 218, areceive beamformer 220, a RF processor 224, a RF/IQ buffer 226, a userinput module 230, a signal processor 240, an image buffer 250, a displaysystem 260, an archive 270, and a training engine 280.

The transmitter 202 may comprise suitable circuitry, interfaces, logic,and/or code that may be operable to drive an ultrasound probe 204. Theultrasound probe 204 may comprise a two dimensional (2D) array ofpiezoelectric elements. The ultrasound probe 204 may comprise a group oftransmit transducer elements 206 and a group of receive transducerelements 208, that normally constitute the same elements. In certainembodiment, the ultrasound probe 204 may be operable to acquireultrasound image data covering at least a substantial portion of ananatomy, such as the heart, a blood vessel, or any suitable anatomicalstructure.

The transmit beamformer 210 may comprise suitable circuitry, interfaces,logic, and/or code that may be operable to control the transmitter 202which, through a transmit sub-aperture beamformer 214, drives the groupof transmit transducer elements 206 to emit ultrasonic transmit signalsinto a region of interest (e.g., human, animal, underground cavity,physical structure and the like). The transmitted ultrasonic signals maybe back-scattered from structures in the object of interest, like bloodcells or tissue, to produce echoes. The echoes are received by thereceive transducer elements 208.

The group of receive transducer elements 208 in the ultrasound probe 204may be operable to convert the received echoes into analog signals,undergo sub-aperture beamforming by a receive sub-aperture beamformer216 and are then communicated to a receiver 218. The receiver 218 maycomprise suitable circuitry, interfaces, logic, and/or code that may beoperable to receive the signals from the receive sub-aperture beamformer216. The analog signals may be communicated to one or more of theplurality of A/D converters 222.

The plurality of A/D converters 222 may comprise suitable circuitry,interfaces, logic, and/or code that may be operable to convert theanalog signals from the receiver 218 to corresponding digital signals.The plurality of A/D converters 222 are disposed between the receiver218 and the RF processor 224. Notwithstanding, the disclosure is notlimited in this regard. Accordingly, in some embodiments, the pluralityof A/D converters 222 may be integrated within the receiver 218.

The RF processor 224 may comprise suitable circuitry, interfaces, logic,and/or code that may be operable to demodulate the digital signalsoutput by the plurality of A/D converters 222. In accordance with anembodiment, the RF processor 224 may comprise a complex demodulator (notshown) that is operable to demodulate the digital signals to form I/Odata pairs that are representative of the corresponding echo signals.The RF or I/O signal data may then be communicated to an RF/IQ buffer226. The RF/IQ buffer 226 may comprise suitable circuitry, interfaces,logic, and/or code that may be operable to provide temporary storage ofthe RF or I/O signal data, which is generated by the RF processor 224.

The receive beamformer 220 may comprise suitable circuitry, interfaces,logic, and/or code that may be operable to perform digital beamformingprocessing to, for example, sum the delayed channel signals receivedfrom RF processor 224 via the RF/IQ buffer 226 and output a beam summedsignal. The resulting processed information may be the beam summedsignal that is output from the receive beamformer 220 and communicatedto the signal processor 240. In accordance with some embodiments, thereceiver 218, the plurality of A/D converters 222, the RF processor 224,and the beamformer 220 may be integrated into a single beamformer, whichmay be digital. In various embodiments, the ultrasound system 200comprises a plurality of receive beamformers 220.

The user input device 230 may be utilized to input patient data, scanparameters, settings, select protocols and/or templates, interact withan artificial intelligence segmentation processor to select trackingtargets, and the like. In an example embodiment, the user input device230 may be operable to configure, manage and/or control operation of oneor more components and/or modules in the ultrasound system 200. In thisregard, the user input device 230 may be operable to configure, manageand/or control operation of the transmitter 202, the ultrasound probe204, the transmit beamformer 210, the receiver 218, the receivebeamformer 220, the RF processor 224, the RF/IQ buffer 226, the userinput device 230, the signal processor 240, the image buffer 250, thedisplay system 260, and/or the archive 270. The user input device 230may include button(s), rotary encoder(s), a touchscreen, motiontracking, voice recognition, a mouse device, keyboard, camera and/or anyother device capable of receiving a user directive.

In certain embodiments, one or more of the user input devices 230 may beintegrated into other components, such as the display system 260 or theultrasound probe 204, for example. As an example, user input device 230may include a touchscreen display. As another example, user input device230 may include an accelerometer, gyroscope, and/or magnetometerattached to and/or integrated with the probe 204 to provide gesturemotion recognition of the probe 204, such as to identify one or moreprobe compressions against a patient body, a pre-defined probe movementor tilt operation, or the like. Additionally and/or alternatively, theuser input device 230 may include image analysis processing to identifyprobe gestures by analyzing acquired image data.

The signal processor 240 may comprise suitable circuitry, interfaces,logic, and/or code that may be operable to process ultrasound scan data(i.e., summed IQ signal) for generating ultrasound images forpresentation on a display system 260. The signal processor 240 isoperable to perform one or more processing operations according to aplurality of selectable ultrasound modalities on the acquired ultrasoundscan data. In an example embodiment, the signal processor 240 may beoperable to perform display processing and/or control processing, amongother things. Acquired ultrasound scan data may be processed inreal-time during a scanning session as the echo signals are received.Additionally or alternatively, the ultrasound scan data may be storedtemporarily in the RF/IQ buffer 226 during a scanning session andprocessed in less than real-time in a live or off-line operation. Invarious embodiments, the processed image data may be presented at thedisplay system 260 and/or may be stored at the archive 270. The archive270 may be a local archive, a Picture Archiving and Communication System(PACS), or any suitable device for storing images and relatedinformation.

The signal processor 240 may be one or more central processing units,microprocessors, microcontrollers, and/or the like. The signal processor240 may be an integrated component, or may be distributed across variouslocations, for example. The signal processor 240 may be configured forreceiving input information from the user input device 230 and/or thearchive 270, generating an output displayable by the display system 260,and manipulating the output in response to input information from theuser input device 230, among other things. The signal processor 240 maybe capable of executing any of the method(s) and/or set(s) ofinstructions discussed herein in accordance with the variousembodiments, for example.

The ultrasound system 200 may be operable to continuously acquireultrasound scan data at a frame rate that is suitable for the imagingsituation in question. Typical frame rates range from 20-220 but may belower or higher. The acquired ultrasound scan data may be displayed onthe display system 260 at a display-rate that may be the same as theframe rate, or slower or faster. The image buffer 250 is included forstoring processed frames of acquired ultrasound scan data that are notscheduled to be displayed immediately. Preferably, the image buffer 250is of sufficient capacity to store at least several minutes' worth offrames of ultrasound scan data. The frames of ultrasound scan data arestored in a manner to facilitate retrieval thereof according to itsorder or time of acquisition. The image buffer 250 may be embodied asany known data storage medium.

In an example embodiment, the signal processor 240 may comprise acardiopulmonary resuscitation (CPR) feedback module 242, which comprisessuitable circuitry, interfaces, logic, and/or code that may beconfigured to perform and/or support various functions relating toproviding and/or facilitating ultrasound imaging with real-time feedbackfor cardiopulmonary resuscitation (CPR).

In some implementations, the signal processor 240 (and/or componentsthereof, such as the CPR feedback module 242) may be configured toimplement and/or use deep learning techniques and/or algorithms, such asusing deep neural networks (e.g., a convolutional neural network),and/or may utilize any suitable form of artificial intelligence imageanalysis techniques or machine learning processing functionalityconfigured to, e.g., analyze acquired ultrasound images, such as toidentify, segment, label, and track structures meeting particularcriteria and/or having particular characteristics. The CPR feedbackmodule 242 may be configured for utilizing these techniques and/orcapabilities in facilitating or supporting real-time feedback forcardiopulmonary resuscitation (CPR) compressions. For example, the CPRfeedback module 242 may be configured to identify structures pertinentto evaluation CPR compressions, such as the aorta, the aortic outlet,the left ventricular (LV), the left ventricular outflow tract (LVOT),etc.

In an example implementation, the signal processor 240 (and/orcomponents thereof, such as the CPR feedback module 242) may be providedas a deep neural network that may be made up of, for example, an inputlayer, an output layer, and one or more hidden layers in between theinput and output layers. Each of the layers may be made up of aplurality of processing nodes that may be referred to as neurons.

For example, the deep neural network may include an input layer having aneuron for each pixel or a group of pixels from a scan plane of ananatomical structure. The output layer may have a neuron correspondingto a plurality of pre-defined structures or types of structures. Eachneuron of each layer may perform a processing function and pass theprocessed ultrasound image information to one of a plurality of neuronsof a downstream layer for further processing. As an example, neurons ofa first layer may learn to recognize edges of structure in theultrasound image data. The neurons of a second layer may learn torecognize shapes based on the detected edges from the first layer. Theneurons of a third layer may learn positions of the recognized shapesrelative to landmarks in the ultrasound image data. The processingperformed by the deep neural network (e.g., convolutional neuralnetwork) may identify biological and/or artificial structures inultrasound image data with a high degree of probability.

In certain implementations, the signal processor 240 (and/or componentsthereof, such as the CPR feedback module 242) may be configured toperform or otherwise control at least some of the functions performedthereby based on a user instruction via the user input device 230. As anexample, a user may provide a voice command, probe gesture, buttondepression, or the like to issue a particular instruction, such as toprovide real-time feedback during CPR operations, as described below.

The training engine 280 may comprise suitable circuitry, interfaces,logic, and/or code that may be operable to train the neurons of the deepneural network(s) of the signal processor 240 (and/or componentsthereof, such as the CPR feedback module 242). For example, the signalprocessor 240 (and/or components thereof, such as the CPR feedbackmodule 242) may be trained to identify particular structures or types ofstructures provided in an ultrasound scan plane, with the trainingengine 280 training the deep neural network(s) thereof to perform someof the required functions, such as using databases(s) of classifiedultrasound images of various structures.

As an example, the training engine 280 may be configured to utilizeultrasound images of particular structures to train the signal processor240 (and/or components thereof, such as the CPR feedback module 242)with respect to the characteristics of the particular structure(s), suchas the appearance of structure edges, the appearance of structure shapesbased on the edges, the positions of the shapes relative to landmarks inthe ultrasound image data, and the like. In various embodiments, thedatabases of training images may be stored in the archive 270 or anysuitable data storage medium. In certain embodiments, the trainingengine 280 and/or training image databases may be external system(s)communicatively coupled via a wired or wireless connection to theultrasound system 200.

In operation, the ultrasound system 200 may be used in generatingultrasonic images, including two-dimensional (2D), three-dimensional(3D), and/or four-dimensional (4D) images. In this regard, theultrasound system 200 may be operable to continuously acquire ultrasoundscan data at a particular frame rate, which may be suitable for theimaging situation in question. For example, frame rates may range from20-70 but may be lower or higher. The acquired ultrasound scan data maybe displayed on the display system 260 at a display-rate that may be thesame as the frame rate, or slower or faster. An image buffer 250 isincluded for storing processed frames of acquired ultrasound scan datanot scheduled to be displayed immediately. Preferably, the image buffer250 is of sufficient capacity to store at least several seconds' worthof frames of ultrasound scan data. The frames of ultrasound scan dataare stored in a manner to facilitate retrieval thereof according to itsorder or time of acquisition. The image buffer 250 may be embodied asany known data storage medium.

In some instances, the ultrasound system 200 may be configured tosupport grayscale and color based operations. For example, the signalprocessor 240 may be operable to perform grayscale B-mode processingand/or color processing. The grayscale B-mode processing may compriseprocessing B-mode RF signal data or IQ data pairs. For example, thegrayscale B-mode processing may enable forming an envelope of thebeam-summed receive signal by computing the quantity (I²+Q²)^(1/2). Theenvelope may undergo additional B-mode processing, such as logarithmiccompression to form the display data. The display data may be convertedto X-Y format for video display. The scan-converted frames may be mappedto grayscale for display. The B-mode frames that are provided to theimage buffer 250 and/or the display system 260. The color processing maycomprise processing color based RF signal data or IQ data pairs to formframes to overlay on B-mode frames that are provided to the image buffer250 and/or the display system 260. The grayscale and/or color processingmay be adaptively adjusted based on user input—e.g., a selection fromthe user input device 230, for example, for enhance of grayscale and/orcolor of particular area.

In some instances, ultrasound imaging may include generation and/ordisplay of volumetric ultrasound images—that is where objects (e.g.,organs, tissues, etc.) are displayed three-dimensional 3D. In thisregard, with 3D (and similarly 4D) imaging, volumetric ultrasounddatasets may be acquired, comprising voxels that correspond to theimaged objects. This may be done, e.g., by transmitting the sound wavesat different angles rather than simply transmitting them in onedirection (e.g., straight down), and then capture their reflectionsback. The returning echoes (of transmissions at different angles) arethen captured, and processed (e.g., via the signal processor 240) togenerate the corresponding volumetric datasets, which may in turn beused in creating and/or displaying volume (e.g. 3D) images, such as viathe display 250. This may entail use of particular handling techniquesto provide the desired 3D perception. For example, volume renderingtechniques may be used in displaying projections (e.g., 2D projections)of the volumetric (e.g., 3D) datasets. In this regard, rendering a 2Dprojection of a 3D dataset may comprise setting or defining a perceptionangle in space relative to the object being displayed, and then definingor computing necessary information (e.g., opacity and color) for everyvoxel in the dataset. This may be done, for example, using suitabletransfer functions for defining RGBA (red, green, blue, and alpha) valuefor every voxel.

In various implementations in accordance with the present disclosure,the ultrasound system 200 may be configured to support ultrasoundimaging with real-time feedback for cardiopulmonary resuscitation (CPR)compressions. In this regard, in some instances, ultrasound systems suchas the ultrasound system 200 may be configured for supporting ultrasoundimaging in conjunction with cardiopulmonary resuscitation (CPR). Forexample, the ultrasound system 200 may be configured to generate anddisplay ultrasound images while performing cardiopulmonary resuscitation(CPR) on a patient. To facilitate such use, the ultrasound system 200may be adaptively designed and/or configured. For example, the probe 204may be configured as transesophageal echocardiogram (TEE) probe ortransthoracic echocardiogram (TTE) probe, which may allow transmittingand receiving ultrasound images in manner compatible with performing CPRand without interfering with these operations—e.g., in the parasternalview, which don't interfere with the compressions. Further, theultrasound system 200 may be designed and/or implemented to belightweight and/or portable, such that it may be mobile (and as such maybe easily moved to and used on location where CPR is being performed).

Further, the ultrasound system 200 may be configured to providereal-time feedback to the user relating to the CPR operations (e.g., theCPR compressions being applied to the patient). In this regard, theultrasound system 200 may be configured to generate the feedback, whichmay entail determining any information pertaining to the generation offeedback, and to provide (e.g., via suitable output device) thefeedback. The feedback may comprise, for example, real-time visualfeedback. In this regard, the ultrasound system 200 may be configured togenerate the visual feedback, and to display the visual feedback, aswell to perform any pertinent operations (e.g., determining informationrelating to the feedback, formatting the feedback, incorporating thefeedback, etc.). For example, visual feedback may be done byincorporating generated visual feedback into the ultrasound images asthey are displayed.

The real-time feedback may comprise feedback relating to compressionsapplied by the user during CPR, such as positioning of thecompression—e.g., whether or not the position or location where thecompression are applied is (or not) the correct and/or optimal position.For example, the ultrasound system 200 may be configured to, whilecompressions are being applied, identify structures pertinent to CPR(e.g., the aorta, the aortic outlet, the left ventricular (LV), and theleft ventricular outflow tract (LVOT), etc.), to continually determinelocation of each compression, to determine area where majority of thecompressions is applied, and to compare that area with location(s) ofidentified structure(s). This area are may be referred as the “maximalcompression area.” The ultrasound system 200 may be configured to usedifferent criteria for determining what constitute “majority” of thecompression. The ultrasound system 200 may determine that area based on,for example, where more than half of the compressions are applied.Alternatively, in some instances a particular threshold (e.g., presetminimal percent of total compressions) may be used in assessing when a“majority” of compressions are applied in particular area.

Once determined, the maximal compression area may then be assessed todetermine if the majority of compressions are applied correctly. In thisregard, ideally CPR compressions should be above the left ventricle, andas such if CPR compressions may be assessed as being applied correctlyif the maximal compression area corresponds to that location. Theultrasound system 200 may generate and provide CPR positioning feedback(e.g., visual feedback) based on such assessment.

For example, if the compressions are applied in a correct location, theultrasound system 200 may provide a visual feedback indicating that(e.g., a green indicator over that area); if the compressions areapplied in an incorrect location, the ultrasound system 200 may providea different visual feedback indicating the incorrect location ofcompression (e.g., a red indicator over that area). In some instances,addition visual feedback may be provided. For example, where the maximalcompression area corresponds to incorrect location, in addition toproviding the incorrect location indication, the ultrasound system 200may also provide additional visual feedback to assist the user incorrecting the location (e.g., an arrow pointing to the direction thatthe user should reposition the hands for continuing compressions, forexample, showing that the compressions be moved in the medial or lateraldirection).

In some instances, the ultrasound system 200 may be configured toprovide other types of feedback, beyond and/or in addition tolocation-related feedback. For example, the ultrasound system 200 may beconfigured to determine and provide feedback (e.g., visual feedback)relating to information pertinent to CPR operation. The ultrasoundsystem 200 may be configured to, for example, track and/or determine CRPcompression rate, and to generate and provide feedback (e.g., visualfeedback) relating thereto.

For example, the ultrasound system 200 may be configured to calculatethe volume flow rate, and to generate and display the waveform of thecalculated carotid blood flow. In this regard, during CPR the user coulduse the patch probe for monitoring the carotid blood flow whichindicates if an adequate amount of blood flows to the brain with eachcompression. The ultrasound system 200 may display the waveform, andaccording to the calculated flow rate, may provide a correspondingvisual feedback (e.g., red indicator), indicating that the compressionposition is incorrect. The waveform peaks may be used to calculate thecompressions rate, and the number may be shown, either by itself aloneor in conjunction with the recommended rate of compressions in CPR(e.g., 100-120 compressions per minute). In this regard, the feedbackmay be visually altered to indicate whether the compression rate iscorrect or not. For example, if the actual compression rate is lowerthan minimal recommended rate (e.g., 100 compressions per minute), thecompression rate may be marked particular manner (e.g., in red).

In some instances, the ultrasound system 200 may be configured toprovide non-visual feedback, such as audible. For example, theultrasound system 200 may be configured to generate and output a warningaudible beep to indicate any issues with the CPR operations as beingperformed—e.g., incorrect position/location, incorrect compression rate,etc. This may be done with or without providing visual feedback too.

In some instances, the ultrasound system 200 may be configured to storedata relating to CPR operations, to enable improving the accuracy andeffectiveness of CPR operations. For example, the ultrasound system 200may be configured to store and retrieve images that correspond tospecific body zone of the patients on whom CPR is performed.

Consequently, implementations in accordance with the present disclosuremay enhance cardiopulmonary resuscitation (CPR) operations by providingusers (e.g., physicians, clinicians) real-time feedback about theeffectiveness of the CPR (e.g., the CPR compressions being applied), towarn the users when something is not being done correctly and/oroptimally (e.g., location of compressions), and to indicate how to makecorrections (e.g., how to correct the location and/or position of thehands), thus allowing for immediately improving the quality of thecompressions which are the main factor for success of CPR.

FIG. 3 illustrates an example ultrasound image showing the heart andsurrounding area, which may be generated via an ultrasound systemconfigured for supporting cardiopulmonary resuscitation (CPR) operationsin accordance with the present disclosure. Shown in FIG. 3 is ascreenshot of an ultrasound image 300.

The ultrasound image 300 may represent an ultrasound image of a heartand surrounding area generated when performing ultrasound imaging duringcardiopulmonary resuscitation (CPR), in a system implemented inaccordance with the present disclosure, such as the ultrasound system200 of FIG. 2. In particular, the ultrasound image 300 may represent anultrasound image of a heart and surrounding area. In this regard, theultrasound image 300 may be generated when performing ultrasound imagingduring cardiopulmonary resuscitation (CPR). Thus, such ultrasound imagesmay include such structures and/or areas as the heart champers (of whichthe left ventricle (LV), right ventricle (RV), and left atrium (LA) areshown in FIG. 3).

In accordance with the present disclosure, ultrasound images generatedduring cardiopulmonary resuscitation (CPR) may be processed to supportproviding real-time feedback relating to the CPR. For example, theultrasound images (or datasets corresponding thereto) may be processedto such that the images (or areas included therein) may be automaticallysegmented. The segmenting may be directed to particular structuresand/or areas that are pertinent to CPR compressions.

For example, segmenting the ultrasound image frames, and the segmentsmay be matched to corresponding structures or areas, to enableidentifying segments that match structures/areas pertinent to CPR—e.g.,the left ventricle (LV) 302. The location of each compression may betracked, and matched to the corresponding segment. The segment that ismost compressed over time may then be calculated or determined, asexplained above.

The most compressed segment may then be assessed for determining whether(or not) it correspond to a correction position for applying CPRcompressions, such as by determining if the most contracted segment ispart of the LV 302 (or other pertinent parts/structures, such as the ofthe aorta, etc.). That determination may be used in generating and/orconfiguring feedback (e.g., visual feedback), as illustrated in FIG. 4.

FIG. 4 illustrates example ultrasound images that incorporate real-timevisual feedback relating to location of cardiopulmonary resuscitation(CPR) compressions, in accordance with the present disclosure. Shown inFIG. 4 are screenshots of ultrasound images 400 and 420.

The ultrasound images 400 and 420 may represent ultrasound images of aheart and surrounding area that are generated when performing ultrasoundimaging during cardiopulmonary resuscitation (CPR), in a systemimplemented in accordance with the present disclosure, such as theultrasound system 200 of FIG. 2. In particular, the ultrasound images400 and 420 illustrated example real-time visual feedback that may beprovided during example use scenario of the ultrasound image 200 whenused in conjunction with conduction CPR on a patient.

As explained above, the locations of compressions may be monitoredand/or determined—e.g., based on processing of ultrasound images (ordatasets corresponding thereto), and correspondingly, the maximalcompression area may be determined. The maximal compression area (orlocation thereof) may then be compared with the location determined asbeing the “correct” location for applying CPR compressions. In thisregard, the correct location may correspond to particular pertinentstructures, such as the LV. A visual feedback may then be generatedand/or configured based on the outcome of the comparison, and appliedinto displayed ultrasound images.

For example, as shown in the example implementation shown in FIG. 4, thevisual feedback may be a visual indicator (e.g., line) over the maximalcompression area, and having different characteristics based on theoutcome of the assessment of the maximal compression area. Thus, if themaximal compression area corresponds to incorrect position (e.g., overthe aortic outlet, as shown in image 400, or over the left ventricularoutflow tract (LVOT)), a visual indictor 402 indicating an incorrectposition may be generated and configured in particular manner (e.g., asred line) to indicate to the user that the compressions are generallyapplied in the wrong position. If the maximal compression areacorresponds to correct position (e.g., over the left ventricle, as shownin image 420), a visual indictor 422 indicating a correct position maybe generated and configured in particular manner (e.g., as green line)to indicate to the user that the compressions are generally applied inthe correct position.

In some instances, additional visual feedback may be generated andprovided. For example, while not shown in FIG. 4, in addition toincluding the visual indicator 402 (for indicating incorrect position),a visual feedback may additionally be incorporated in ultrasound image402 to help aid the user in applying the compressions the correctposition—e.g., an arrow may be generated and display showing the userhow to correct the hands' position (e.g., pointing to the areacorresponding to the LV).

FIG. 5 illustrates example ultrasound images that incorporate real-timevisual feedback relating to location of cardiopulmonary resuscitation(CPR) compressions, in accordance with the present disclosure. Shown inFIG. 5 are screenshots of ultrasound image 500.

The ultrasound image 500 may represent an example ultrasound image of aheart and surrounding area generated when performing ultrasound imagingduring cardiopulmonary resuscitation (CPR), in a system implemented inaccordance with the present disclosure, such as the ultrasound system200 of FIG. 2. In particular, the ultrasound image 500 illustratesexample real-time visual feedback that may be provided during exampleuse scenario of the ultrasound image 200 when used in conjunction withconduction CPR on a patient.

Specifically, the ultrasound image 500 shows use of additional visualfeedback beyond location-related visual feedback. For example, as shownin FIG. 5, the ultrasound image 500 incorporates a location visualindicator 502, which (as shown in FIG. 5) indicates a correct positionfor the majority of applied compressions. In this regard, as describedabove, the location visual indicator may be generated and/or configuredbased on determination of the maximal compression area (e.g., bytracking location of each compression over time), and assessment thereof(e.g., based on comparison of the location of the maximal compressionarea with the location of structures where compressions should beapplied, such as the left ventricle (LV)).

However, the ultrasound image 500 includes additional visual feedbackrelating to the CPR operations. For example, as shown in FIG. 5, theultrasound image 500 includes visual feedback relating to thecompression rate. In this regard, the compression rate may be determinedin various ways, such as based on flow calculation as explained above.For example, the compression rate may be calculated from waveform peaksof the carotid flow, as described above.

Once determined, the compression rate may be displayed on the ultrasoundimage. In this regard, the manner the compression rate is displayed(e.g., visually) may be changed based on pertinent criteria. Thus, wherethe compression rate as calculated (e.g., 90 as shown in FIG. 5) isdetermined to be below a particular value or range, which be predefinedas recommended range (e.g., 100-120 compressions per minute), thecalculated compression rate may be displayed in red. Conversely, whenthe calculated compression rate is within the recommended range, it maybe displayed in green.

FIG. 6 illustrates a flowchart of an example steps that may be performedfor ultrasound imaging with ultrasound imaging with real-time feedbackfor cardiopulmonary resuscitation (CPR) compressions.

Shown in FIG. 6 is flow chart 600, comprising a plurality of examplesteps (represented as blocks 602-614), which may be performed in asuitable system (e.g., system 200 of FIG. 2) for ultrasound imaging withreal-time feedback for cardiopulmonary resuscitation (CPR).

In start step 602, the system may be setup, and operations may initiate.

In step 604, ultrasound signals may be transmitted, and correspondingechoes of the signals may be received.

In step 606, the received echoes of the ultrasound signals may beprocessed, to generate corresponding datasets for use in generatingultrasound images.

In step 608, based on processing of the ultrasound images (orcorresponding datasets), structures pertinent to CPR may be identified.

In step 610, based on processing of the ultrasound images (orcorresponding datasets), information relating to CPR—e.g., location ofcompressions over time, compression rate, etc.

In step 612, corresponding real-time feedback (incl. visual feedback)may be determined based on determined CPR related informationcorresponding real-time feedback (incl. visual feedback).

In step 614, the real-time feedback may be provided to the user,including displaying visual feedback (e.g., overlaid on displayedultrasound images).

An example ultrasound system, in accordance with the present disclosure,for use in support of cardiopulmonary resuscitation (CPR) operationscomprises an ultrasound probe configured to transmit ultrasound signalsand receive echo ultrasound signals; a display configured to displayultrasound images; and one or more circuits configured to processultrasound images generated based on received echo ultrasound signalsduring cardiopulmonary resuscitation (CPR) of a patient; determine basedon the processing of the ultrasound images, real-time informationrelating to the cardiopulmonary resuscitation (CPR); generate based onthe information, feedback for assisting in conducting thecardiopulmonary resuscitation (CPR). The feedback comprises informationand/or indications relating to compressions applied during thecardiopulmonary resuscitation (CPR); is configured for output duringdisplaying of the generated ultrasound images.

In an example implementation, the one or more circuits are configured tosegment each ultrasound image into a plurality of segments; determine inwhich segment of the plurality of segments a location where eachcompression is applied; and continuously identify which segment of theplurality of segment is where a majority of compressions are appliedover time.

In an example implementation, the one or more circuits are configured todetermine a maximal compression area, wherein the maximal compressionarea corresponds to a location where a majority of compressions areapplied; and assess based on one or more criteria associated withcardiopulmonary resuscitation (CPR), whether the maximal compressionarea corresponds to a correct position or an incorrect position.

In an example implementation, the one or more circuits are configured togenerate different indicators based on determination that the maximalcompression area corresponds to the correct position or the incorrectposition.

In an example implementation, the one or more circuits are configured togenerate indication for adjusting location where compressions areapplied to match the correct position.

In an example implementation, the one or more circuits are configured todetermine based on the processing of the ultrasound images, location ofone or more structures pertinent to the cardiopulmonary resuscitation(CPR); and compare location where each compression is applied withlocation of each of the one or more structures. The one or morestructures may comprise aorta, aortic outlet, left ventricular (LV), andleft ventricular outflow tract (LVOT)

An example method, in accordance with the present disclosure, forsupporting cardiopulmonary resuscitation (CPR) operations comprisesprocessing ultrasound images generated based on received echo ultrasoundsignals during cardiopulmonary resuscitation (CPR) of a patient;determining based on the processing of the ultrasound images, real-timeinformation relating to the cardiopulmonary resuscitation (CPR);generating based on the information, feedback for assisting inconducting the cardiopulmonary resuscitation (CPR). The feedbackcomprises information and/or indications relating to compressionsapplied during the cardiopulmonary resuscitation (CPR); and isconfigured for outputting during displaying of the generated ultrasoundimages.

In an example implementation, the method further comprises segmentingeach ultrasound image into a plurality of segments; determining in whichsegment of the plurality of segments a location where each compressionis applied; and continuously identifying which segment of the pluralityof segment is where a majority of compressions are applied over time.

In an example implementation, the method further comprises determining amaximal compression area, wherein the maximal compression areacorresponds to a location where a majority of compressions are applied;and assessing based on one or more criteria associated withcardiopulmonary resuscitation (CPR), whether the maximal compressionarea corresponds to a correct position or an incorrect position.

In an example implementation, the method further comprises generatingdifferent indicators based on determination that the maximal compressionarea corresponds to the correct position or the incorrect position.

In an example implementation, the method further comprises generating anindication for adjusting location where compressions are applied tomatch the correct position.

In an example implementation, the method further comprises determiningbased on the processing of the ultrasound images, location of one ormore structures pertinent to the cardiopulmonary resuscitation (CPR);and comparing location where each compression is applied with locationof each of the one or more structures. The one or more structures maycomprise aorta, aortic outlet, left ventricular (LV), and leftventricular outflow tract (LVOT).

An example non-transitory computer readable medium, in accordance withthe present disclosure, may have stored thereon a computer programhaving at least one code section, the at least one code section beingexecutable in an ultrasound device for causing the ultrasound device tosupport of cardiopulmonary resuscitation (CPR) operations, by performingone or more steps that comprise processing ultrasound images generatedbased on received echo ultrasound signals during cardiopulmonaryresuscitation (CPR) of a patient; determining based on the processing ofthe ultrasound images, real-time information relating to thecardiopulmonary resuscitation (CPR); and generating based on theinformation, feedback for assisting in conducting the cardiopulmonaryresuscitation (CPR). The feedback comprises information and/orindications relating to compressions applied during the cardiopulmonaryresuscitation (CPR); and is configured for outputting during displayingof the generated ultrasound images.

In an example implementation, the one or more steps further comprisesegmenting each ultrasound image into a plurality of segments;determining in which segment of the plurality of segments a locationwhere each compression is applied; and continuously identifying whichsegment of the plurality of segment is where a majority of compressionsare applied over time.

In an example implementation, the one or more steps further comprisedetermining a maximal compression area, wherein the maximal compressionarea corresponds to a location where majority of compressions areapplied; and assessing based on one or more criteria associated withcardiopulmonary resuscitation (CPR), whether the maximal compressionarea corresponds to a correct position or an incorrect position.

In an example implementation, the one or more steps further comprisegenerating different indicators based on determination that the maximalcompression area corresponds to the correct position or the incorrectposition.

In an example implementation, the one or more steps further comprisegenerating an indication for adjusting location where compressions areapplied to match the correct position.

In an example implementation, processing the ultrasound images furthercomprises determining based on the processing of the ultrasound images,location of one or more structures pertinent to the cardiopulmonaryresuscitation (CPR); and comparing location where each compression isapplied with location of each of the one or more structures. The maycomprise aorta, aortic outlet, left ventricular (LV), and leftventricular outflow tract (LVOT).

As utilized herein the terms “circuits” and “circuitry” refer tophysical electronic components (e.g., hardware) and any software and/orfirmware (“code”) which may configure the hardware, be executed by thehardware, and or otherwise be associated with the hardware. As usedherein, for example, a particular processor and memory may comprise afirst “circuit” when executing a first one or more lines of code and maycomprise a second “circuit” when executing a second one or more lines ofcode. As utilized herein, “and/or” means any one or more of the items inthe list joined by “and/or”. As an example, “x and/or y” means anyelement of the three-element set {(x), (y), (x, y)}. In other words, “xand/or y” means “one or both of x and y.” As another example, “x, y,and/or z” means any element of the seven-element set {(x), (y), (z), (x,y), (x, z), (y, z), (x, y, z)}. In other words, “x, y and/or z” means“one or more of x, y, and z.” As utilized herein, the terms “block” and“module” refer to functions than can be performed by one or morecircuits. As utilized herein, the term “exemplary” means serving as anon-limiting example, instance, or illustration. As utilized herein, theterms “for example” and “e.g.,” set off lists of one or morenon-limiting examples, instances, or illustrations. As utilized herein,circuitry is “operable” to perform a function whenever the circuitrycomprises the necessary hardware (and code, if any is necessary) toperform the function, regardless of whether performance of the functionis disabled or not enabled (e.g., by some user-configurable setting, afactory trim, etc.).

Other embodiments of the invention may provide a non-transitory computerreadable medium and/or storage medium, and/or a non-transitory machinereadable medium and/or storage medium, having stored thereon, a machinecode and/or a computer program having at least one code sectionexecutable by a machine and/or a computer, thereby causing the machineand/or computer to perform the processes as described herein.

Accordingly, the present disclosure may be realized in hardware,software, or a combination of hardware and software. The presentinvention may be realized in a centralized fashion in at least onecomputing system, or in a distributed fashion where different elementsare spread across several interconnected computing systems. Any kind ofcomputing system or other apparatus adapted for carrying out the methodsdescribed herein is suited. A typical combination of hardware andsoftware may be a general-purpose computing system with a program orother code that, when being loaded and executed, controls the computingsystem such that it carries out the methods described herein. Anothertypical implementation may comprise an application specific integratedcircuit or chip.

Various embodiments in accordance with the present disclosure may alsobe embedded in a computer program product, which comprises all thefeatures enabling the implementation of the methods described herein,and which when loaded in a computer system is able to carry out thesemethods. Computer program in the present context means any expression,in any language, code or notation, of a set of instructions intended tocause a system having an information processing capability to perform aparticular function either directly or after either or both of thefollowing: a) conversion to another language, code or notation; b)reproduction in a different material form.

While the present invention has been described with reference to certainembodiments, it will be understood by those skilled in the art thatvarious changes may be made and equivalents may be substituted withoutdeparting from the scope of the present invention. In addition, manymodifications may be made to adapt a particular situation or material tothe teachings of the present invention without departing from its scope.Therefore, it is intended that the present invention not be limited tothe particular embodiment disclosed, but that the present invention willinclude all embodiments falling within the scope of the appended claims.

What is claimed is:
 1. An ultrasound system for use in support ofcardiopulmonary resuscitation (CPR) operations, the system comprising:an ultrasound probe configured to transmit ultrasound signals andreceive echo ultrasound signals; a display configured to displayultrasound images; and one or more circuits configured to: processultrasound images generated based on received echo ultrasound signalsduring cardiopulmonary resuscitation (CPR) of a patient; determine basedon the processing of the ultrasound images, real-time informationrelating to the cardiopulmonary resuscitation (CPR); and generate basedon the information, feedback for assisting in conducting thecardiopulmonary resuscitation (CPR); wherein: the feedback comprisesinformation and/or indications relating to compressions applied duringthe cardiopulmonary resuscitation (CPR); and the feedback is configuredfor output during displaying of the generated ultrasound images.
 2. Theultrasound system of claim 1, wherein the one or more circuits areconfigured to: segment each ultrasound image into a plurality ofsegments; determine in which segment of the plurality of segments alocation where each compression is applied; and continuously identifywhich segment of the plurality of segment is where a majority ofcompressions are applied over time.
 3. The ultrasound system of claim 1,wherein the one or more circuits are configured to: determine a maximalcompression area, wherein the maximal compression area corresponds to alocation where a majority of compressions are applied; and assess basedon one or more criteria associated with cardiopulmonary resuscitation(CPR), whether the maximal compression area corresponds to a correctposition or an incorrect position.
 4. The ultrasound system of claim 3,wherein the one or more circuits are configured to generate differentindicators based on determination that the maximal compression areacorresponds to the correct position or the incorrect position.
 5. Theultrasound system of claim 4, wherein the one or more circuits areconfigured to generate indication for adjusting location wherecompressions are applied to match the correct position.
 6. Theultrasound system of claim 1, wherein the one or more circuits areconfigured to: determine based on the processing of the ultrasoundimages, location of one or more structures pertinent to thecardiopulmonary resuscitation (CPR); and compare location where eachcompression is applied with location of each of the one or morestructures.
 7. A method for supporting cardiopulmonary resuscitation(CPR) operations, the method comprising: processing ultrasound imagesgenerated based on received echo ultrasound signals duringcardiopulmonary resuscitation (CPR) of a patient; determining based onthe processing of the ultrasound images, real-time information relatingto the cardiopulmonary resuscitation (CPR); and generating based on theinformation, feedback for assisting in conducting the cardiopulmonaryresuscitation (CPR); wherein: the feedback comprises information and/orindications relating to compressions applied during the cardiopulmonaryresuscitation (CPR); and the feedback is configured for outputtingduring displaying of the generated ultrasound images.
 8. The method ofclaim 7, further comprising: segmenting each ultrasound image into aplurality of segments; determining in which segment of the plurality ofsegments a location where each compression is applied; and continuouslyidentifying which segment of the plurality of segment is where amajority of compressions are applied over time.
 9. The method of claim7, further comprising: determining a maximal compression area, whereinthe maximal compression area corresponds to a location where a majorityof compressions are applied; and assessing based on one or more criteriaassociated with cardiopulmonary resuscitation (CPR), whether the maximalcompression area corresponds to a correct position or an incorrectposition.
 10. The method of claim 9, comprising generating differentindicators based on determination that the maximal compression areacorresponds to the correct position or the incorrect position.
 11. Themethod of claim 10, comprising generating an indication for adjustinglocation where compressions are applied to match the correct position.12. The method of claim 7, further comprising: determining based on theprocessing of the ultrasound images, location of one or more structurespertinent to the cardiopulmonary resuscitation (CPR); and comparinglocation where each compression is applied with location of each of theone or more structures.
 13. The method of claim 12, wherein the one ormore structures comprise aorta, aortic outlet, left ventricular (LV),and left ventricular outflow tract (LVOT).
 14. A non-transitory computerreadable medium having stored thereon, a computer program having atleast one code section, the at least one code section being executablein an ultrasound device for causing the ultrasound device to for causingthe ultrasound device to support of cardiopulmonary resuscitation (CPR)operations, by performing one or more steps comprising: processingultrasound images generated based on received echo ultrasound signalsduring cardiopulmonary resuscitation (CPR) of a patient; determiningbased on the processing of the ultrasound images, real-time informationrelating to the cardiopulmonary resuscitation (CPR); and generatingbased on the information, feedback for assisting in conducting thecardiopulmonary resuscitation (CPR); wherein: the feedback comprisesinformation and/or indications relating to compressions applied duringthe cardiopulmonary resuscitation (CPR); and the feedback is configuredfor outputting during displaying of the generated ultrasound images. 15.The non-transitory computer readable medium of claim 14, the one or moresteps further comprising: segmenting each ultrasound image into aplurality of segments; determining in which segment of the plurality ofsegments a location where each compression is applied; and continuouslyidentifying which segment of the plurality of segment is where amajority of compressions are applied over time.
 16. The non-transitorycomputer readable medium of claim 14, the one or more steps furthercomprising: determining a maximal compression area, wherein the maximalcompression area corresponds to a location where majority ofcompressions are applied; and assessing based on one or more criteriaassociated with cardiopulmonary resuscitation (CPR), whether the maximalcompression area corresponds to a correct position or an incorrectposition.
 17. The non-transitory computer readable medium of claim 16,the one or more steps further comprising generating different indicatorsbased on determination that the maximal compression area corresponds tothe correct position or the incorrect position.
 18. The non-transitorycomputer readable medium of claim 17, the one or more steps furthercomprising generating an indication for adjusting location wherecompressions are applied to match the correct position.
 19. Thenon-transitory computer readable medium of claim 14, wherein processingthe ultrasound images comprises: determining based on the processing ofthe ultrasound images, location of one or more structures pertinent tothe cardiopulmonary resuscitation (CPR); and comparing location whereeach compression is applied with location of each of the one or morestructures.
 20. The non-transitory computer readable medium of claim 19,wherein the one or more structures comprise aorta, aortic outlet, leftventricular (LV), and left ventricular outflow tract (LVOT).